Abstract
Swarm robotics is an emerging field that is expected to provide robust solutions to spatially distributed problems. Human operators will often be required to guide a swarm in the fulfillment of a mission. Occasionally, large tasks may require multiple spatial swarms to cooperate in their completion. We hypothesize that when latency and bandwidth significantly restrict communication among human operators, human organizations that promote individual initiative perform more effectively and resiliently than hierarchies in the cooperative best-m-of-n task. Simulations automating the behavior of hub-based swarm robotic agents and simulated groups of human operators are used to evaluate this hypothesis. To make the comparisons between the team and hierarchies meaningful, we explore parameter values determining how simulated human operators behave in teams and hierarchies to optimize the performance of the respective organizations. We show that simulation results generally support the hypothesis with respect to the effect of latency and bandwidth on organizational performance.
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References
Bavelas, A.: Communication patterns in task-oriented groups. J. Acoust. Soc. Am. 22(6), 725–730 (1950)
Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems, vol. 1. Oxford University Press, Oxford (1999)
Brown, D.S., Kerman, S.C., Goodrich, M.A.: Human-swarm interactions based on managing attractors. In Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction, pp. 90–97. ACM (2014)
Castello, E., et al.: Adaptive foraging for simulated and real robotic swarms: the dynamical response threshold approach. Swarm Intell. 10(1), 1–31 (2016)
Coppin, G., Legras, F.: Autonomy spectrum and performance perception issues in swarm supervisory control. Proc. IEEE 100(3), 590–603 (2012). https://doi.org/10.1109/JPROC.2011.2174103. ISSN 0018–9219
Coppin, G., Legras, F.: Controlling swarms of unmanned vehicles through user-centered commands. In: AAAI Fall Symposium: Human Control of Bioinspired Swarms, pp. 21–25 (2012)
Crandall, J.W., et al.: Human-swarm interaction as shared control: achieving flexible fault-tolerant systems. In: Harris, D. (ed.) EPCE 2017. LNCS (LNAI), vol. 10275, pp. 266–284. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-58472-0_21
Cummings, M.L., Guerlain, S.: Developing operator capacity estimates for supervisory control of autonomous vehicles. Hum. Factors 49(1), 1–15 (2007)
Flap, H., Bulder, B., Beate, V., et al.: Intra-organizational networks and performance: a review. Comput. Math. Organ. Theory 4(2), 109–147 (1998)
Garnier, S., Gautrais, J., Theraulaz, G.: The biological principles of swarm intelligence. Swarm Intell. 1(1), 3–31 (2007)
Guetzkow, H., Simon, H.A.: The impact of certain communication nets upon organization and performance in task-oriented groups. Manage. Sci. 1(3–4), 233–250 (1955)
Jung, S.-Y., Brown, D.S., Goodrich, M.A.: Shaping Couzin-like torus swarms through coordinated mediation. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1834–1839. IEEE (2013)
Kolling, A., Sycara, K., Nunnally, S., Lewis, M.: Human swarm interaction: an experimental study of two types of interaction with foraging swarms. J. Hum.-Robot Interact. 2(2), 103–129 (2013)
Leavitt, H.J., Mueller, R.A.H.: Some effects of feedback on communication. Hum. Relat. 4(4), 401–410 (1951)
Lee, D., Franchi, A., Giordano, P.R., Son, H.I., Bülthoff, H.H.: Haptic teleoperation of multiple unmanned aerial vehicles over the internet. In: 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 1341–1347. IEEE (2011)
Miller, C.A., Funk, H.B., Dorneich, M., Whitlow, S.D.: A playbook interface for mixed initiative control of multiple unmanned vehicle teams. In: Proceedings of the 21st Digital Avionics Systems Conference, 2002, Proceedings, vol. 2, pp. 7E4–7E4. IEEE(2002)
Navarro, F.: An introduction to swarm robotics. ISRN Robot. 2013, 1–10 (2012)
Nevai, A.L., Passino, K.M., Srinivasan, P.: Stability of choice in the honey bee nest-site selection process. J. Theor. Biol. 263(1), 93–107 (2010)
Niku, S.B.: Introduction to Robotics: Analysis, Systems, Applications, vol. 7. Prentice Hall, Upper Saddle River (2001)
Pendleton, B., Goodrich, M.: Scalable human interaction with robotic swarms. In: AIAA Infotech@ Aerospace (I@ A) Conference, p. 4731 (2013)
Rubenstein, M., Ahler, C., Nagpal, R.: Kilobot: a low cost scalable robot system for collective behaviors. In: 2012 IEEE International Conference on Robotics and Automation (ICRA), pp. 3293–3298. IEEE (2012)
Schmickl, T., Hamann, H.: BEECLUST: a swarm algorithm derived from honeybees. In: Bio-Inspired Computing and Communication Networks. CRC Press, March 2011
Shaw, M.E.: Some effects of unequal distribution of information upon group performance in various communication nets. J. Abnorm. Soc. Psychol. 49(4p1), 547 (1954)
Steiner, I.D.: Group Processes and Group Productivity. Academic Press, New York (1972)
Steinfeld, A., Jenkins, O.C., Scassellati, B.: The Oz of wizard: simulating the human for interaction research. In: Proceedings of the 4th ACM/IEEE International Conference on Human Robot Interaction, pp. 101–108. ACM (2009)
Valentini, G., Ferrante, E., Dorigo, M.: The best-of-n problem in robot swarms: formalization, state of the art, and novel perspectives. Front. Robot. AI 4 (2017). https://doi.org/10.3389/frobt.2017.00009
Wilson, S., et al.: Pheeno, a versatile swarm robotic research and education platform. IEEE Robot. Autom. Lett. 1(2), 884–891 (2016)
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The work in this paper was supported by a grant from the US Office of Naval Research under grant number N000141613025. All opinions, findings, and results are the responsibility of the authors and not the sponsoring organization.
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Grosh, J.R., Goodrich, M.A. (2020). Multi-human Management of Robotic Swarms. In: Kurosu, M. (eds) Human-Computer Interaction. Multimodal and Natural Interaction. HCII 2020. Lecture Notes in Computer Science(), vol 12182. Springer, Cham. https://doi.org/10.1007/978-3-030-49062-1_41
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